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Foundational skills for Neuroimaging: Philosophy, Mathematics, and Statistics, and Other Essential Skills
Provider: Faculty of Health and Medical Sciences

Activity no.: 3472-19-00-00 
Enrollment deadline: 21/12/2018
Date and time17.01.2019, at: 09:00 - 26.04.2019, at: 12:00
Regular seats15
Course fee6,600.00 kr.
LecturersOliver Hulme
ECTS credits2.40
Contact personSusanne Steffensen    E-mail address: susannes@drcmr.dk
Enrolment Handling/Course OrganiserPhD administration     E-mail address: fak-phdkursus@sund.ku.dk

Aim and content
This course is free of charge for PhD students at Danish universities (except Copenhagen Business School). All other participants must pay the course fee.
Anyone can apply for the course, but if you are not a PhD student, you will be placed on the waiting list for the course until enrollment deadline. After the deadline of enrollment, available seats will be allocated to students on the waiting list.

Learning objectives
A student who has met the objectives of the course will be able to:

1. Understand and articulate the basic philosophical assumptions of scientific methods, with particular emphasis on falsification, and theory testing, particularly as it applies to modern neuroimaging
2. Understand and apply basic mathematical tools from algebra to calculus
3. Understand and apply basic concepts in frequentist statistics, including hypothesis-testing, power, multiple linear regression
4. Understand and apply basic concepts in ”new statistics” with a greater emphasis on effect size estimation and confidence intervals, as well as Bayesian statistics, and to develop an understanding of the limitations of the classical framework
5. Begin a programme of neuroimaging training equipped with most of the foundational skills necessary to learn effectively.

This is a foundation skills course that provides many of the basic skills necessary to do neuroimaging research. Topics covered include philosophical foundations (inc. deduction, induction, falsification, inference), mathematical foundations (inc. algebra, matrices, calculus), statistical foundations (inc. central limit theorem, hypothesis testing, power, linear regression, anova, confidence intervals & effect size estimation, and Bayesian statistics). Whilst it is contextualised and oriented towards neuroimaging problems, it does not include content on actual neuroimaging methods.

Some programming experience with Matlab is essential. If you do not have this experience, it is possible to take video based coursera courses in Matlab alongside this course (in your own time). Familiarity with high school mathematics is recommended. As the course is explicitly designed for students from all backgrounds and training, no other prerequisites are required.

Relevance to graduate programmes
The course is particularly relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH, and to any graduate programme requiring basic training in statistical methods.

Basic Metabolic Research
Public Health and Epidemiology
Medical and Molecular imaging


14x2 hours lectures + 14x1 hour exercises

Course director
Oliver Hulme, Senior Researcher, Danish Research Centre for Magnetic Resonance, oliverh@drcmr.dk

Oliver Hulme, Senior Researcher, Danish Research Centre for Magnetic Resonance
David Meder, Postdoc, Danish Research Centre for Magnetic Resonance
+ Teaching assistants

Beginning 17th Jan 2019, ending 26th April 2019. Note: no lecture on 18th April
All lectures are Thursday mornings, between 9-12am (Lecture 9-11, exercises 11-12)

Course location
Danish Research Centre for Magnetic Resonance
Pavillion 7 meeting room (upper floor)
MR-forskning, Afs. 714
Copenhagen University Hospital Hvidovre
Kettegard Allé 30

Please register before 17 December 2019

Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules.

Applications from other participants will be considered after the last day of enrolment.

Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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